Dielectric optical coatings are crucial for ultrafast laser systems. Current methods for designing these coatings rely on brute force optimization, which is computationally intensive and demands expert knowledge. Our project introduces an AI-driven approach using deep neural networks to solve this complex inverse problem, offering faster, expert-independent solutions.
In-situ grazing-incidence small-angle X-ray scattering (GISAXS) is a powerful technique for investigating nanoscale structures with high time resolution, yet data analysis is complex and time-intensive. To accelerate this process, we present a novel two-step approach that integrates physics-informed deep learning to extract key morphological parameters. The approach involves preprocessing...
With a holographic setup, full-field projections can be obtained with a single exposure. Reconstruction of the complex refractive index of the sample is typically done in post-processing and requires many manual steps and time. The need for post-processing prevents an immediate optical evaluation of the measurement results during beamtime and complicates in-situ experiments. We propose a novel...
The European XFEL at DESY is a world-leading research infrastructure in Hamburg, enabling scientists to observe and investigate microstructural processes with resolutions on the atomic and femtosecond scale. To improve the performance of the accelerator, it is essential to optimize the EuXFEL for operation in continuous-wave (CW) mode. Despite its advantages, an operation in CW mode requires a...
Phase retrieval from amplitude-only measurements is a common task that appears in diverse scientific fields. Recognizing the conceptual similarity between ptychographic measurements and the short-time Fourier transform (STFT), often used in audio processing, our interdisciplinary research focuses on phase retrieval methods in these two domains. We present several recent contributions...
In X-ray Computed Tomography (CT), obtaining projections from various angles is crucial for 3D reconstruction. To adapt CT for real-time quality control, it's essential to reduce the scan angles while preserving reconstruction quality. Sparse-angle tomography, which achieves 3D reconstructions with fewer data, necessitates selecting the most informative angles—a challenge equivalent to solving...
